Abnormality determination device and abnormality determination method

Abstract

An abnormality determination device include: a learning unit configured to provide an abnormality detection model for detecting an abnormality of a facility by machine learning using log data that represent operation performance of the facility; a determination unit configured to input data representing operation performance of a target facility and determine an abnormality of the target facility; and an output unit configured to output a determination result by the determination unit. If the determination result is different from an evaluation result of an on-site checking of the target facility, the learning unit is configured to update the abnormality detection model based on the evaluation result.

1 . An abnormality determination device comprising:
 a learning unit configured to provide an abnormality detection model for detecting an abnormality of a facility by machine learning using log data that represent operation performance of the facility;   a determination unit configured to input data representing operation performance of a target facility and determine an abnormality of the target facility; and   an output unit configured to output a determination result by the determination unit, wherein   if the determination result is different from an evaluation result of an on-site checking of the target facility, the learning unit is configured to update the abnormality detection model based on the evaluation result.   
     
     
         2 . The abnormality determination device according to  claim 1 , further comprising
 a comparison unit configured to make a comparison of the determination result with the evaluation result, wherein   if the determination result is different from the evaluation result, the learning unit is configured to update the abnormality detection model based on the evaluation result.   
     
     
         3 . The abnormality determination device according to  claim 2 , wherein if the determination result indicates that the target facility is abnormal, the comparison unit is configured to make the comparison, and if the determination result indicates that the target facility is normal, the comparison unit is configured not to make the comparison. 
     
     
         4 . The abnormality determination device according to any one of  claim 1 , wherein
 if the determination result indicates that the target facility is abnormal, the output unit is configured to output the determination result, and   if the determination result indicates that the target facility is normal, the output unit is configured not to output the determination result.   
     
     
         5 . The abnormality determination device according to any one of  claim 1 , further comprising an acquisition unit configured to acquire the evaluation result. 
     
     
         6 . The abnormality determination device according to any one of  claim 1 , further comprising a storage unit configured to store the log data and the abnormality detection model. 
     
     
         7 . A method of determining an abnormality, comprising:
 creating an abnormality detection model, for detecting an abnormality of a facility, by machine learning using log data representing operation performance of the facility;   determining an abnormality of a target facility by inputting data representing operation performance of the target facility to the abnormality detection model; and   outputting a result obtained by said determining of the abnormality, wherein   if the result is different from an evaluation result of the target facility by an on-site checking, said creating the abnormality detection model comprises updating the abnormality detection model based on the evaluation result.   
     
     
         8 . A program for causing a computer to execute the method according to  claim 7 . 
     
     
         9 . A recording medium recording a program for causing a computer to execute the method according to  claim 7 .